Notes from Code For America’s Day of Civic Hacking

  • Donna Hilliard, Code Tenderloin
  • Jay Cheng, SF Chamber of Commerce
  • Fernando Marti, Council of Community Housing Organizations
  • Karen Chapple, Professor and Chair of City and Regional Planning, UC Berkeley
  • Marion Wellington, TechEquity Collaborative

Talks

Things I already believed:

  • SF rents are rising at a rate disproportionate to the median salary, forcing existing residents out of the city.
  • SF is not building enough housing to meet the demand of people wanting to live here.
  • The housing SF does build is largely aimed at higher income residents.
  • New apartments go up in only a small part of SF, geographically. This is largely due to zoning laws in large swaths of the city restricting new property to single-family usage.
  • This is probably not a problem that tech can solve on it’s own, it needs top-down leadership to implement comprehensive solutions.
Jay Cheng’s hilarious and sad diagram of the convoluted approval process for new housing

What I was surprised to learn:

  • About 50,000 units of housing are approved each year, yet only 5,000 are actually built. The cost of construction is high, including material and labor. Regulations also add to the cost. Unless these costs get cheaper, rents will have actually have to go up for most of these projects to be profitable.
  • Lots of what is getting built and purchased has relatively low occupancy (investment/second homes).
  • The partitioning of SF into 11 districts has made it easier to reject housing. The supervisor of each district has veto power over any housing project proposed in their district, and they hold their residents above all else. This is an unfortunate incentive, as the people who would benefit from these housing projects do not live in these districts yet.
  • There is a chicken-and-egg problem when it comes to transit and housing. We want to build transit that connects existing housing, and we want to build housing near existing transit. This makes it difficult for areas not already close to transit to “catch up”.

Hackathon

  • Data can help us understand the efficacy of different policies. Tech can be used to visualize this data to help inform politicians and voters.
  • Tech can connect people to solve coordination problems. Karen Chapple brought up “Accessory Dwelling Units”, which can be both profitable for existing residents and a useful way to build more housing, but sometimes requires residents to share their properties. (Not sure I totally understood this)
  • There are a lot of people in SF who do care about housing. Tech can help them make personal choices that align with their values.

Takeaway

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